Operations Research, Systems Engineering and Industrial Engineering Commons^™

Partial Adjustable Autonomy In Multi-Agent Environment And Its Application To Military Logistics, Hoong Chuin Lau, Lucas Agussurja, Ramesh Thangarajoo

Research Collection School Of Computing and Information Systems

In a rapidly changing environment, the behavior and decision-making power of agents may have to be adaptive with respect to a fluctuating autonomy. In this paper, a centralized fuzzy approach is proposed to sense changes in environmental conditions and translate them to changes in agent autonomy. A distributed coalition formation scheme is then applied to allow agents in the new autonomy to renegotiate to establish schedule consistency. The proposed framework is applied to a real-time logistics control of a military hazardous material storage facility under peace-to-war transition.

Knowledge Representation, Organization, And Formalization For Simulation Modeling Of Discrete Manufacturing System, Jung Hung Ma

All-Inclusive List of Electronic Theses and Dissertations

Simulation is an useful tool that helps managers making decision by designing models for real systems. It helps companies to study behaviors of real systems hy analyzing computer models and improve the systems based on the experiments' results. However, cross-domain knowledge requirement and lack of tools facilitate modeling are the main reasons that make industries hesitate to use simulation to assist making decision. This research is an attempt to develop robust knowledge representations for discrete manufacturing system and conceptual simulation model. A modeling methodology was proposed to utilize these knowledge representations (KRs) for developing conceptual simulation models from application domain …

Dispatching Vehicles In A Mega Container Terminal, Ebru K. Bish, Frank Y. Chen, Thin Yin Leong, Barry L. Nelson, Jonathan W. C. Ng, David Simchi-Levi

Research Collection School Of Computing and Information Systems

We consider a container terminal discharging and uploading containers to and from ships. The discharged containers are stored at prespecified storage locations in the terminal yard. Containers are moved between the ship area and the yard using a fleet of vehicles, each of which can carry one container at a time. The problem is to dispatch vehicles to the containers so as to minimize the total time it takes to serve a ship, which is the total time it takes to discharge all containers from the ship and upload new containers onto the ship. We develop easily implementable heuristic algorithms …

Evaluation Of Time-Varying Availability In Multi-Echelon Inventory System With Combat Damage, Hoong Chuin Lau, Huawei Song

Research Collection School Of Computing and Information Systems

The models for multi-echelon inventory systems in existing literatures predominantly address failures due to reliability in peacetime. In wartime or even peacetime operational scenarios, unexpected combat damage can cause a large number of systems to be heavily damaged, to the extent that they become irreparable. In this paper, we study a multi-echelon spare parts support system under combat damage, discuss the replenishment policy and propose an approximate method to evaluate the time-varying system performance operational availability considering the effect of passivation. Experiments show our model works well and efficiently against simulation.

Tuning Tabu Search Strategies Via Visual Diagnosis, Steven Halim, Wee Chong Wan, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

While designing working metaheuristics can be straightforward, tuning them to solve the underlying combinatorial optimization problem well can be tricky. Several tuning methods have been proposed but they do not address the new aspect of our proposed classification of the metaheuristic tuning problem: tuning search strategies. We propose a tuning methodology based on Visual Diagnosis and a generic tool called Visualizer for Metaheuristics Development Framework(V-MDF) to address specifically the problem of tuning search (particularly Tabu Search) strategies. Under V-MDF, we propose the use of a Distance Radar visualizer where the human and computer can collaborate to diagnose the occurrence of …

Exploiting Belief Bounds: Practical Pomdps For Personal Assistant Agents, Pradeep Varakantham, Rajiv Maheswaran, Milind Tambe

Research Collection School Of Computing and Information Systems

Agents or agent teams deployed to assist humans often face the challenges of monitoring the state of key processes in their environment (including the state of their human users themselves) and making periodic decisions based on such monitoring. POMDPs appear well suited to enable agents to address these challenges, given the uncertain environment and cost of actions, but optimal policy generation for POMDPs is computationally expensive. This paper introduces three key techniques to speedup POMDP policy generation that exploit the notion of progress or dynamics in personal assistant domains. Policy computation is restricted to the belief space polytope that remains …

Approximate Strategic Reasoning Through Hierarchical Reduction Of Large Symmetric Games, Michael P. Wellman, Daniel M. Reeves, Kevin M. Lochner, Shih-Fen Cheng, Rahul Suri

Research Collection School Of Computing and Information Systems

To deal with exponential growth in the size of a game with the number of agents, we propose an approximation based on a hierarchy of reduced games. The reduced game achieves savings by restricting the number of agents playing any strategy to fixed multiples. We validate the idea through experiments on randomly generated local-effect games. An extended application to strategic reasoning about a complex trading scenario motivates the approach, and demonstrates methods for game-theoretic reasoning over incompletely-specified games at multiple levels of granularity.

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design: Quarterly Progress Report January 1-March 31, 2005, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The Advanced Fuel Cycle Initiative (AFCI) and Transmutation Research Program-University Participation Program (TRP-UPP) supported by Department of Energy of the United States have been developing many important technologies for the transmutation of nuclear waste to address long-term disposal issues. While successfully embedding AMUSE module into a dedicated System Engineering Model (TRPSEMPro), developed by the Nevada Center for Advanced Computational Methods (NCACM) at the University of Nevada-Las Vegas collaborating with Argonne National Laboratory (ANL), ANL is interested in further simulating the Light Water Reactor (LWR) Spent Fuel Treatment Facility (SFTF) combining commercial process simulation and analysis packages and core calculation of …

Optimal Sampling Of A Chemical Hazard Area, Jennifer R. Plourde

Theses and Dissertations

This thesis proposes a methodology for optimally sampling a chemical hazard area subsequent to a chemical weapons attack. The objective is to identify the maximum number of areas that no longer require protective gear for safe operations. We model the area as an undirected graph and employ network analysis techniques to provide a methodological framework for identifying an optimal sampling sequence within a fixed time limit. We propose four models that characterize the secondary vapor concentrations: i) static and deterministic, ii) static and stochastic, iii) dynamic and deterministic, and iv) dynamic and stochastic. Comparisons of the static cases and their …

Passwords: A Survey On Usage And Policy, Kurt W. Martinson

Theses and Dissertations

Computer password use is on the rise. Passwords have become one of the primary authentication methods used today. It is because of their high use that organizations have started to place parameters on passwords. Are password restrictions a nuisance? What are some of the consequences that result as organizations place the burden of their computer security on passwords? This thesis analyzes the results of a survey instrument that was used to determine if individuals are using similar techniques or patterns when choosing or remembering their passwords. It also looks at how individuals feel about using passwords. In addition, the authors …

Reinforcement Learning-Based Output Feedback Control Of Nonlinear Systems With Input Constraints, Pingan He, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel neural network (NN) -based output feedback controller with magnitude constraints is designed to deliver a desired tracking performance for a class of multi-input-multi-output (MIMO) discrete-time strict feedback nonlinear systems. Reinforcement learning in discrete time is proposed for the output feedback controller, which uses three NN: 1) a NN observer to estimate the system states with the input-output data; 2) a critic NN to approximate certain strategic utility function; and 3) an action NN to minimize both the strategic utility function and the unknown dynamics estimation errors. The magnitude constraints are manifested as saturation nonlinearities in the output feedback …

A Multi-Server Markovian Queueing Model With Primary And Secondary Services, Valentina Klimenok, Srinivas R. Chakravarthy, Alexander Dudin

Industrial & Manufacturing Engineering Presentations And Conference Materials

We study a multi-server queueing model in which the arrivals occur according to a Markovian arrival process. An arriving customer either (a) is lost due to all main servers being busy; or (b) enters into service with one of the main servers and leaves the system (as a satisfied primary customer); (c) enters into a service with one of the main servers, gets service in self-service mode, and is impatient to get a final service with one of the main servers, may leave the system (as a dissatisfied secondary customer); or (d) enters into service with one of the main …

Software Development Project Risk Management: A Literature Review, Kevin Macg. Adams, C. Ariel Pinto

Engineering Management & Systems Engineering Faculty Publications

The rapid and unprecedented growth in software has brought with it some of the most spectacular and costly project failures in modern history. How risk management is presented in the scholarly journals may give insight into the risk management methods and techniques in use on software development projects. This paper provides a glimpse into the risk management methods, methodologies and techniques available to those who are responsible for software development projects by conducting a non-experimental content analysis. The findings reveal that risk management has not received sufficient attention and does not appear to be widely accepted within the software engineering …

A Robust Controller For The Manipulation Of Micro Scale Objects, Qinmin Yang, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A suite of novel robust controllers is presented for the manipulation and handling of micro-scale objects in a micro-electromechanical system (MEMS) where adhesive, surface tension, friction and van der Waals forces are dominant. Moreover, these forces are typically unknown. The robust controller overcomes the unknown system dynamics and ensures the performance in the presence of actuator constraints by assuming that the upper bounds on these forces are known. On the other hand, for the robust adaptive controller, the unknown forces are estimated online. Using the Lyapunov approach, the uniformly ultimate boundedness (UUB) of the closed-loop manipulation error is shown for …

Decentralized Discrete-Time Neural Network Controller For A Class Of Nonlinear Systems With Unknown Interconnections, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

A novel decentralized neural network (NN) controller in discrete-time is designed for a class of uncertain nonlinear discrete-time systems with unknown interconnections. Neural networks are used to approximate both the uncertain dynamics of the nonlinear systems and the unknown interconnections. Only local signals are needed for the decentralized controller design and the stability of the overall system can be guaranteed using the Lyapunov analysis. Further, controller redesign for the original subsystems is not required when additional subsystems are appended. Simulation results demonstrate the effectiveness of the proposed controller. The NN does not require an offline learning phase and the weights …

Energy-Efficient Rate Adaptation Mac Protocol For Ad Hoc Wireless Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Resource constraints in ad hoc wireless networks require that they are energy efficient during both transmission and rate adaptation. In this paper, we propose a novel energy-efficient rate adaptation protocol that selects modulation schemes online to maximize throughput based on channel state while saving energy. This protocol uses the distributed power control (DPC) algorithm (M. Zawodniok et al., 2004) to accurately determine the necessary transmission power and to reduce the energy consumption. Additionally, the transmission rate is altered using energy efficiency as a constraint to meet the required throughput, which is estimated with queue fill ratio. Moreover, back-off scheme is …

Neural Network-Based Control Of Nonlinear Discrete-Time Systems In Non-Strict Form, Jagannathan Sarangapani, Zheng Chen, Pingan He

Electrical and Computer Engineering Faculty Research & Creative Works

A novel reinforcement learning-based adaptive neural network (NN) controller, also referred as the adaptive-critic NN controller, is developed to deliver a desired tracking performance for a class of non-strict feedback nonlinear discrete-time systems in the presence of bounded and unknown disturbances. The adaptive critic NN controller architecture includes a critic NN and two action NNs. The critic NN approximates certain strategic utility function whereas the action neural networks are used to minimize both the strategic utility function and the unknown dynamics estimation errors. The NN weights are tuned online so as to minimize certain performance index. By using gradient descent-based …

Predictive Congestion Control Mac Protocol For Wireless Sensor Networks, Maciej Jan Zawodniok, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. …

Block Phase Correlation-Based Automatic Drift Compensation For Atomic Force Microscopes, Qinmin Yang, Eric W. Bohannan, Jagannathan Sarangapani

Electrical and Computer Engineering Faculty Research & Creative Works

Automatic nanomanipulation and nanofabrication with an Atomic Force Microscope (AFM) is a precursor for nanomanufacturing. In ambient conditions without stringent environmental controls, nanomanipulation tasks require extensive human intervention to compensate for the many spatial uncertainties of the AFM. Among these uncertainties, thermal drift is especially hard to solve because it tends to increase with time and cannot be compensated simultaneously by feedback. In this paper, an automatic compensation scheme is introduced to measure and estimate drift. This information can be subsequently utilized to compensate for the thermal drift so that a real-time controller for nanomanipulation can be designed as if …

Development Of A Systems Engineering Model Of The Chemical Separations Process, Yitung Chen, Darrell Pepper, Sean Hsieh

Separations Campaign (TRP)

The chemical processing of used nuclear fuel is an integral component of any strategy for the transmutation of nuclear waste. Due to the large volume of material that must be handled in this first step of the transmutation process, the efficiency of the separations process is a key factor in the potential economic viability of transmutation strategies. The ability to optimize the chemical separation systems is vital to ensure the feasibility of the transmutation program.

Systems analysis, or total systems modeling, is one of the strongest tools available to researchers for understanding and optimizing complex systems such as chemical separations …

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The major objective is to create a framework that combines all the strengths of AMUSE’s complicated calculations, well established commercial system process package such as ASPENPLUS, HYSYS and PRO/II and TRPSEMPro’s flexible parameter optimization modules. Development of the process simulation code can be done using the solvent extraction process experience at Argonne National Laboratory and in collaboration with the NCACM.

The major activities of the task are the following:

• Develop a framework for simulating the SFTF process using AMUSE code, commercial process package, such as ASPEN- PLUS, and system engineering model.
• Develop a middleware package that can communicate between the …

A Multi-Agent Approach For Solving Optimization Problems Involving Expensive Resources, Hoong Chuin Lau, H. Wang

Research Collection School Of Computing and Information Systems

In this paper, we propose a multi-agent approach for solving a class of optimization problems involving expensive resources, where monolithic local search schemes perform miserably. More specifically, we study the class of bin-packing problems. Under our proposed Fine-Grained Agent System scheme, rational agents work both collaboratively and selfishly based on local search and mimic physics-motivated systems. We apply our approach to a generalization of bin-packing - the Inventory Routing Problem with Time Windows - which is an important logistics problem, and demonstrate the efficiency and effectiveness of our approach.

Robust Temporal Constraint Networks, Hoong Chuin Lau, Thomas Ou, Melvyn Sim

Research Collection School Of Computing and Information Systems

In this paper, we propose the Robust Temporal Constraint Network (RTCN) model for simple temporal constraint networks where activity durations are bounded by random variables. The problem is to determine whether such temporal network can be executed with failure probability less than a given 0 ≤ E ≤ 1 for each possible instantiation of the random variables, and if so. how one might find a feasible schedule with each given instantiation. The advantage of our model is that one can vary the value of ∊ to control the level of conservativeness of the solution. We present a computationally tractable and …

Development Of Integrated Process Simulation System Model For Spent Fuel Treatment Facility (Sftf) Design: Quarterly Report October 1-December 31, 2004, Yitung Chen, Sean Hsieh

Separations Campaign (TRP)

The Advanced Fuel Cycle Initiative (AFCI) and Transmutation Research Program- University Participation Program (TRP-UPP) supported by Department of Energy of the United States have been developing many important technologies for the transmutation of nuclear waste to address long-term disposal issues. While successfully embedding AMUSE module into a dedicated System Engineering Model (TRPSEMPro), developed by the Nevada Center for Advanced Computational Methods (NCACM) at the University of Nevada, Las Vegas collaborating with Argonne National Laboratory (ANL), ANL is interested in further simulating the Light Water Reactor (LWR) Spent Fuel Treatment Facility (SFTF) combining commercial process simulation and analysis packages and core …

Comparative Study Of The Dynamics Of Circulating Fluidized Bed Riser And Downer Of Equal Diameters, Samwel V. Manyele

Tanzania Journal of Engineering and Technology (TJET)

The microscopic flow dynamics of the 100-mm internal diameter riser/downer circulating fluidized bed (CFB) unit were monitored using a solids concentration fiber optic probe. The comparison was conducted by comparing radial profiles Of the dynamic parameters derived from time-series analysis techniques (statistical and chaos analyses). The solids concentration signals used were recorded under similar operating conditions (gas velocity of 8.0 m/s and solids flux of 100 kg/m2s). Similar axial elevations were compared (entrance and fully developed sections of die reactors). A1 each loca!ion, the signals were sampled a! afrequency of 970 Hz for duration of 30 seconds. It was observed …

Comparison Of Sampling Methods For Flatness Evaluation Using Cmm, Ashish Singhal

All-Inclusive List of Electronic Theses and Dissertations

Efficient part feature verification using Coordinate Measuring Machine (CMM) requires efficient sample point selection as well as accurate zone fitting. This work deals with flatness tolerance evaluation and the Least- Square (LS) technique is used to compute tolerance zone. In regard to the sampling strategy there are several methods commonly employed in Coordinate Measuring Machine inspection literature. The appropriate method is selected according to the accuracy requirement, the geometry features of the work piece, and the condition of the machine producing the work piece. This research focuses on the five sampling methods: Hammersley sequence sampling, Halton-Zaremba sequence sampling, Random sampling, …

Corrective Maintenance Optimization In An Air Force, Hoong Chuin Lau, K. Y. Neo, W. C. Wan

Research Collection School Of Computing and Information Systems

Successful military mission planning and execution depend critically on equipment serviceability and resupply. Due to the stochastic nature of demands, the forecast of optimal spares and resources needed to guarantee the level of serviceability is a complex problem, especially in a multi-echelon setting. In this paper, we propose a decision-support concept and software tool known as Corrective Maintenance Optimizer (CMO) that helps to optimize system availability, through proper allocation of spare parts, both strategically and operationally.

Two-Echelon Repairable Item Inventory System With Limited Repair Capacity Under Nonstationary Demands, Hoong Chuin Lau, Huawei Song

Research Collection School Of Computing and Information Systems

We study a repairable item inventory system under limited repair capacity and nonstationary Poisson demands, motivated by corrective maintenance of military equipment. Our goal is to minimize the cost of both spare and repair resource allocation. We propose an efficient analytical model that combines optimization modeling and queuing theory.

A Periodic-Review Inventory Model With Application To The Continuous-Review Obsolescence Problem, Yuyue Song, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

In this paper we consider a stochastic-demand periodic-review inventory model with sudden obsolescence. We characterize the structure of the optimal policy and propose a dynamic programming algorithm for computing its parameters. We then utilize this algorithm to approximate the solution to the continuous-review sudden obsolescence problem with general obsolescence distribution. We prove convergence of our approximation scheme, and demonstrate it numerically against known closed-form solutions of special cases.

Logistics Network Design With Differentiated Delivery Lead Time: A Chemical Industry Case Study, Michelle Lee Fong Cheong, Rohit Bhatnagar, Stephen C. Graves

Research Collection School Of Computing and Information Systems

Most logistics network design models assume exogenous customer demand that is independent of the service time or level. This paper examines the benefits of segmenting demand according to lead-time sensitivity of customers. To capture lead-time sensitivity in the network design model, we use a facility grouping method to ensure that the different demand classes are satisfied on time. In addition, we perform a series of computational experiments to develop a set of managerial insights for the network design decision making process.